Assembly of polypeptide and protein backbone conformations from low energy ensembles of short fragments: development of strategies and construction of models for myoglobin, lysozyme, and thymosin beta 4.

Recently we developed methods for the construction of knowledge-based mean fields from a data base of known protein structures. As shown previously, this approach can be used to calculate ensembles of probable conformations for short fragments of polypeptide chains. Here we develop procedures for the assembly of short fragments to complete three-dimensional models of polypeptide chains. The amino acid sequence of a given protein is decomposed into all possible overlapping fragments of a given length, and an ensemble of probable conformations is calculated for each fragment. The fragments are assembled to a complete model by choosing appropriate conformations from the individual ensembles and by averaging over equivalent angles. Finally a consistent model is obtained by rebuilding the conformation from the average angles. From the average angles the local variability of the structure can be calculated, which is a useful criterion for the reliability of the model. The procedure is applied to the calculation of the local backbone conformations of myoglobin and lysozyme whose structures have been solved by X-ray analysis and thymosin beta 4, a polypeptide of 43 amino acid residues whose structure was recently investigated by NMR spectroscopy. We demonstrate that substantial fractions of the calculated local backbone conformations are similar to the experimentally determined structures.     

Detection of native-like models for amino acid sequences of unknown three-dimensional structure in a data base of known protein conformations.

We present an approach which can be used to identify native-like folds in a data base of protein conformations in the absence of any sequence homology to proteins in the data base. The method is based on a knowledge-based force field derived from a set of known protein conformations. A given sequence is mounted on all conformations in the data base and the associated energies are calculated. Using several conformations and sequences from the globin family we show that the native conformation is identified correctly. In fact the resolution of the force field is high enough to discriminate between a native fold and several closely related conformations. We then apply the procedure to several globins of known sequence but unknown three dimensional structure. The homology of these sequences to globins of known structures in the data base ranges from 49 to 17%. With one exception we find that for all globin sequences one of the known globin folds is identified as the most favorable conformation. These results are obtained using a force field derived from a data base devoid of globins of known structure. We briefly discuss useful applications in protein structural research and future development of our approach.     

Kinetic studies of folding of the B-domain of staphylococcal protein A with molecular dynamics and a united-residue (UNRES) model of polypeptide chains

Langevin dynamics is used with our physics-based united-residue (UNRES) force field to study the folding pathways of the B-domain of staphylococcal protein A (1BDD (alpha; 46 residues)). With 400 trajectories of protein A started from the extended state (to gather meaningful statistics), and simulated for more than 35 ns each, 380 of them folded to the native structure. The simulations were carried out at the optimal folding temperature of protein A with this force field. To the best of our knowledge, this is the first simulation study of protein-folding kinetics with a physics-based force field in which reliable statistics can be gathered. In all the simulations, the C-terminal alpha-helix forms first. The ensemble of the native basin has an average RMSD value of 4 A from the native structure. There is a stable intermediate along the folding pathway, in which the N-terminal alpha-helix is unfolded; this intermediate appears on the way to the native structure in less than one-fourth of the folding pathways, while the remaining ones proceed directly to the native state. Non-native structures persist until the end of the simulations, but the native-like structures dominate. To express the kinetics of protein A folding quantitatively, two observables were used: (i) the average alpha-helix content (averaged over all trajectories within a given time window); and (ii) the fraction of conformations (averaged over all trajectories within a given time window) with Calpha RMSD values from the native structure less than 5 A (fraction of completely folded structures). The alpha-helix content grows quickly with time, and its variation fits well to a single-exponential term, suggesting fast two-state kinetics. On the other hand, the fraction of folded structures changes more slowly with time and fits to a sum of two exponentials, in agreement with the appearance of the intermediate, found when analyzing the folding pathways. This observation demonstrates that different qualitative and quantitative conclusions about folding kinetics can be drawn depending on which observable is monitored.     

Structural trees for proteins containing φ-motifs

In the present study, a novel structural motif of proteins referred to as the phi-motif is considered, and two novel structural trees in which the phi-motif is taken as the root structure have been constructed. The simplest phi-motif is formed by three adjacent beta-strands connected by loops and packed in one beta-sheet so that its overall fold resembles the Greek letter phi. Construction of the structural trees and modeling of folding pathways have shown that all structures of the protein superfamilies can be obtained by stepwise addition of alpha-helices and/or beta-strands to the root phi-motif taking into account a restricted set of rules inferred from known principles of protein structure. The structural trees are a good tool for structure comparison, structural classification of proteins, as well as for searching for all possible protein folds and folding pathways.     

Comparing atomistic molecular mechanics force fields for a difficult target: a case study on the Alzheimer’s amyloid β-peptide

Macromolecular function arises from structure, and many diseases are associated with misfolding of proteins. Molecular simulation methods can augment experimental techniques to understand misfolding and aggregation pathways with atomistic resolution, but the reliability of these predictions is a function of the parameters used for the simulation. There are many biomolecular force fields available, but most are validated using stably folded structures. Here, we present the results of molecular dynamics simulations on the intrinsically disordered amyloid β-peptide (Aβ), whose misfolding and aggregation give rise to the symptoms of Alzheimer’s disease. Because of the link between secondary structure changes and pathology, being able to accurately model the structure of Aβ would greatly improve our understanding of this disease, and it may facilitate application of modeling approaches to other protein misfolding disorders. To this end, we compared five popular atomistic force fields (AMBER03, CHARMM22 + CMAP, GROMOS96 53A6, GROMOS96 54A7, and OPLS-AA) to determine which could best model the structure of Aβ. By comparing secondary structure content, NMR shifts, and radius of gyration to available experimental data, we conclude that AMBER03 and CHARMM22 + CMAP over-stabilize helical structure within Aβ, with CHARMM22 + CMAP also producing elongated Aβ structures, in conflict with experimental findings. OPLS-AA, GROMOS96 53A6, and GROMOS96 54A7 produce very similar results in terms of helical and β-strand content, calculated NMR shifts, and radii of gyration that agree well with experimental data.     

Accelerated simulation of unfolding and refolding of a large single chain globular protein

We have developed novel strategies for contracting simulation times in protein dynamics that enable us to study a complex protein with molecular weight in excess of 34 kDa. Starting from a crystal structure, we produce unfolded and then refolded states for the protein. We then compare these quantitatively using both established and new metrics for protein structure and quality checking. These include use of the programs Concoord and Darvols. Simulation of protein-folded structure well beyond the molten globule state and then recovery back to the folded state is itself new, and our results throw new light on the protein-folding process. We accomplish this using a novel cooling protocol developed for this work.     

Enhanced sampling of peptide and protein conformations using replica exchange simulations with a peptide backbone biasing-potential

During replica exchange molecular dynamics (RexMD) simulations, several replicas of a system are simulated at different temperatures in parallel allowing for exchange between replicas at frequent intervals. This technique allows significantly improved sampling of conformational space and is increasingly being used for structure prediction of peptides and proteins. A drawback of the standard temperature RexMD is the rapid increase of the replica number with increasing system size to cover a desired temperature range. In an effort to limit the number of replicas, a new Hamiltonian-RexMD method has been developed that is specifically designed to enhance the sampling of peptide and protein conformations by applying various levels of a backbone biasing potential for each replica run. The biasing potential lowers the barrier for backbone dihedral transitions and promotes enhanced peptide backbone transitions along the replica coordinate. The application on several peptide cases including in all cases explicit solvent indicates significantly improved conformational sampling when compared with standard MD simulations. This was achieved with a very modest number of 5-7 replicas for each simulation system making it ideally suited for peptide and protein folding simulations as well as refinement of protein model structures in the presence of explicit solvent.     

Early events in protein folding: Is there something more than hydrophobic burst?

The presence of native contacts in the denatured state of many proteins suggests that elements of the biologically active structure of these molecules are formed during the initial stage of the folding process. The rapidity with which these events take place makes it difficult to study them in vitro, but, by the same token, suitable for studies in silico. With the help of all-atom, explicit solvent, molecular dynamics simulations we have followed in time, starting from elongated structureless conformations, the early events in the folding of src-SH3 domain and of proteins G, L, and CI2. It is observed that within the first 50 ns two important events take place, essentially independent of each other: hydrophobic collapse and formation of a few selected native contacts. The same contacts are also found in simulations carried out in the presence of guanidinium chloride in order to reproduce the conditions used to characterize experimentally the denatured state and testify to the fact that these contacts are to be considered a resilient characterizing property of the denaturated state.     

The interaction of neurotrophins with the p75NTR common neurotrophin receptor: a comprehensive molecular modeling study

Neurotrophins are a family of proteins with pleiotropic effects mediated by two distinct receptor types, namely the Trk family, and the common neurotrophin receptor p75NTR. Binding of four mammalian neurotrophins, nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), neurotrophin-3 (NT-3), and neurotrophin-4/5 (NT-4/5), to p75NTR is studied by molecular modeling based on X-ray structures of the neurotrophins and the extracellular domain of p55TNFR, a homologue of p75NTR. The model of neurotrophin/receptor interactions suggests that the receptor binding domains of neurotrophins (loops I and IV) are geometrically and electrostatically complementary to a putative binding site of p75NTR, formed by the second and part of the third cysteine-rich domains. Geometric match of neurotrophin/receptor binding domains in the complexes, as characterized by shape complementarity statistic Sc, is comparable to known protein/protein complexes. All charged residues within the loops I and IV of the neurotrophins, previously determined as being critical for p75NTR binding, directly participate in receptor binding in the framework of the model. Principal residues of the binding site of p75NTR include Asp47, Lys56, Asp75, Asp76, Asp88, and Glu89. The additional involvement of Arg80 and Glu53 is specific for NGF and BDNF, respectively, and Glu73 participates in binding with NT-3 and NT-4/5. Neurotrophins are likely to induce similar, but not identical, conformational changes within the p75NTR binding site.     

基于知识的蛋白质结构预测

介绍了近几年基于知识的蛋白质三维结构预测方法及其进展．目前,基于知识的结构预测方法主要有两类,一类是同源蛋白模建,这种技术比较成熟,模建的结果可靠性比较高,但只适用于同源性比较高的目标序列的模建;另一类方法即蛋白质逆折叠技术,主要包括3D profile方法和基于势函数的方法,给出的是目标蛋白质的空间走向,它主要可用于序列同源性比较低的蛋白质的结构预测．